The present invention relates to signal processing systems. More specifically, the present invention relates to an aggregate beamformer for use in a directional receiving array such as an array of microphones.
Beamforming is a method of combining signals that are received by an array of sensor elements by adjusting the phase relationships between signals and adding the signals, to cause enhanced sensitivity in a particular direction. Since the array of sensor elements receive the signals at different times, the signals are steered and focused in the desired direction by applying appropriate delays from each array sensor element so that the signals transmitted from a desired point add constructively. The delay for each signal is selected such that a virtual beam is focused at the desired point. In other words, beamforming electronically forms a virtual beam through steering and focusing the signals. Beamforming may serve to determine the location of the target points when it is known which beams detected that target signal. Beams represent the directional response of a system, and the direction of a beam is an angle relative to the array. The beam direction is generally focused to a point, which may or may not be at infinity.
Beamformers are utilized with arrays of electromagnetic and sonic receiving elements, for combining signals of the receiving elements to produce beams of electromagnetic and sonic energy. The term beam is used both for radiant energy received from a particular direction as well as for a beam of transmitted radiant energy since the receiving and transmitting radiation patterns of an array of receiving or radiating elements are identical. Beamformers for receiving arrays employ linear circuits for summing together the signals of the respective receiving elements and for imparting selective delays, or sometimes only phase shifts, to signals of the respective receiving elements. The selection of specific values of time delay is based on the direction of the desired beam relative to the array.
In some situations, the signals of the elements are sampled repetitively to produce sequences of signal samples from each of the elements. The sequences of samples are then transmitted to the beamformer, which forms one or more beams as is desired.
FIG. 1 illustrates a conventional beamformer. If the (sampled) signal at the m-th sensor element is denoted by xm(nxcex94t), where n is the sample number and xcex94t is the time interval between samples, the conventional beamforming procedure results in the output signal y(nxcex94t) according to the equation (1):                               y          ⁡                      (                          n              ⁢                              xe2x80x83                            ⁢              Δ              ⁢                              xe2x80x83                            ⁢              t                        )                          =                              ∑            m                    ⁢                                    W              m                        ⁢                                          x                m                            ⁡                              (                                                      n                    ⁢                                          xe2x80x83                                        ⁢                    Δ                    ⁢                                          xe2x80x83                                        ⁢                    t                                    -                                      d                    m                                                  )                                                                        (        1        )            
wherein
Wm are weight factors that determine the shape of the directional response pattern;
xm(nxcex94t) is the output from sensor element m at time nxcex94t;
xcex94t is the time interval between samples; and
dm are delays that determine the direction in which the response is maximized.
In digital systems, the analog signals xm are sampled and digitized with the delays for each sensor element being an integer number of sample intervals taken as near as possible to the delay necessary for the steered direction (xcex8). Once the signal are converted to digital data they are typically combined by beamforming using weighted sums of the data in tapped delay lines.
The generalized beamformer takes the weighted sum of current and past samples to form the beamformer output. It is more flexible in regard to obtaining desired beam shapes because it allows beam shape to be determined as a function of signal frequency. The counterpart of equation (1) for the generalized beamformer would be             y      ⁢              (                  n          ⁢                      xe2x80x83                    ⁢          Δ          ⁢                      xe2x80x83                    ⁢          t                )              =                  ∑        m            ⁢                        ∑          k                ⁢                              w                          m              ,              k                                ⁢                                    x              m                        ⁢                          (                                                n                  ⁢                                      xe2x80x83                                    ⁢                  Δ                  ⁢                                      xe2x80x83                                    ⁢                  t                                -                k                -                                  d                  m                                            )                                            ,
wherein wm,k are weight factors that determine the shape of the directional response pattern, m is the array component index, and k is an index for the delayed samples.
The generalized formulation can be considered to be a special case of the conventional beamformer expressed by equation (1) if the delayed input signals as treated as separate (virtual) array components (channels) so that the array input channels are xp(nxcex94t)=xm(nxcex94txe2x88x92k), wherein p is an index for the sensor-delay pairs (m,k). In this case, the index p would simply replace the index m in the equation (1).
Since one physical input channel is used for several delayed input channels, more collisions and voids may occur for the generalized beamformer than would be the case where delayed channels are not considered.
A complete state-of-the-art acoustic signal processing system uses a collection of components such as analog to digital converters (ADC), application specific integrated circuits (ASICs), digital signal processors (DSPs), microcontrollers (xcexcC), memory buffers, etc. integrated onto a set of printed circuit boards connected by one or more communications busses. In order to process the data received from the array of sensor elements, the front-end processor, and more specifically the beamformer, is used to process the data from multiple sensor elements substantially all at the same time. The beamformer includes a data acquisition system (DAS) for converting the plurality of sets of data received from the detectors into corresponding signals that can be processed by a signal processor.
Various problems exist with respect to current beamformer designs. The number of circuit components is large, and increases with the number of input signal components, causing high cost and complexity in the designs. The front-end components which provide coupling and anti-alias filtering are not easily integrated into an integrated solid state circuit (IC). A large number of arithmetic operations are required for the calculation of each beam and this number increases with the sampling rate and with the number of sensor elements. The precision to which delays can be realized is limited by the sampling rate (per channel) unless an interpolation filter is used. The circuit and computational complexity generally scales with the number of signal components (channels), making beamformer implementation very expensive or impractical for very large numbers of channels.
Some of these problems can be partially overcome, with associated loss of performance or increase in cost. For example, a multiplexer or switching circuit may be used to share one high speed ADC amongst several signal channels, thereby reducing the number of ADC required but there is generally a trade-off between ADC speed and resolution. The beamformer components subsequent to the ADC involve digital signal processing and can be integrated in an IC or implemented in a high speed digital signal processor (DSP) computer specifically designed for such applications but front-end components are not amenable to low cost integration for arrays of numerous sensor elements, particularly at lower audio frequencies. The large size of the non-integrated components necessitates moving them some distance from the sensor element arrayxe2x80x94requiring a high-bandwidth umbilical cord and driving circuitry in most cases.
The numeric computations can, to some extent, be sped up by using high performance processors that perform them in parallel using redundant computation units or pipeline aspects of the processing. For ultrasound applications, the incoming signal from each sensor element may be shifted to a lower frequency, by a heterodyning circuit, to reduce the subsequent circuit and computational requirements but the heterodyning circuits add cost and complexity, and are subject to variability. The precision to which channel delays can be applied is limited by the sampling interval unless interpolation filters are used to estimate the signal components at times between samples but interpolation is computationally expensive and may be inaccurate.
Arrays of sensors may be designed with sensor elements omitted from their otherwise regular geometry so that the complexity and cost associated with very large number of input channels are reduced. Such arrays are sometimes called sparse arrays. Their design is generally more complex and they do not perform as well as their fully populated equivalents.
As well, multichannel (coder-decoder) codec chips are just now being developed, which provide lower costs per sensor element for digital data acquisition but for very large numbers of sensors this approach also becomes expensive and requires many components.
A beamformer having high resolution, developed for medical ultrasound image scanners, which overcomes or at least reduces the effects of some of these problems, is a DAS using delta-sigma oversampled ADCs, described in U.S. Pat. No. 5,142,286 issued Aug. 25, 1992 in the names of David B. Ribner and Michael A. Wu (the Ribner et al. Patent), which is incorporated herein by reference. The Ribner et al. patent describes a high-resolution ADC using components commonly used to process audio signals for use in processing data from a medical ultrasound imager. Conversion is provided through the use of oversampled, interpolative (or delta-sigma) modulation followed by digital low-pass filtering, typically using a finite impulse response (FIR) filter, and then by decimation. xe2x80x9cOversamplingxe2x80x9d refers to operation of the modulator at a sampling rate many times above the signal Nyquist rate, whereas xe2x80x9cdecimationxe2x80x9d refers to subsampling so as to reduce the sample rate to the Nyquist rate. The ratio Kover of the oversampling rate to the signal Nyquist rate is designated the xe2x80x9coversampling ratioxe2x80x9d. As described in the Ribner et al. Patent, delta-sigma ADCs having single-bit quantizers in the overall feedback loops of their delta-sigma modulators can simplify or eliminate the anti-alias filters for individual acoustic sensor elements by using over-sampling delta-sigma ADCs, which themselves are simpler than conventional converters.
However, while the oversampling delta-sigma modulator and data rate decimator and digital filter as an ADC easily lend themselves to integration fabrication techniques, the required transimpedance pre-amplifier and anti-alias low-pass filter do not. Currently, such analog circuitry would be expensive to fabricate as a part of an integrated chip set including the delta-sigma modulator, probably more expensive than using discrete components based upon current integration techniques. Providing a separate transimpedance preamplifier and analog filter for each sensor element in discrete form as the front end of each sensor element of a DAS, nevertheless adds significant cost to the DAS where, for example, the number of sensor elements needed are on the order of 350 to 1000 sensor elements. Furthermore, a distinct delta-sigma ADC must be provided for each sensor element since the inherent feedback circuitry will not perform the intended function if one delta-sigma ADC is shared by multiplexing the signals from several sensors.
In addition to the foregoing, electronic noise can be a significant problem in DASs used for medical ultrasound imagers, particularly at low level detector signal levels. The design described in the Ribner et al. patent uses a delta-sigma modulator and FIR digital filter. The noise levels of the design tend to remain substantially the same throughout the dynamic range of the input signal.
Recently, there have been developments in integrated acoustic sensor elements. Arrays of acoustic sensor elements for ultrasound applications are a well-developed technology (as in medical ultrasound imaging) but arrays of audio sensor elements integrated on a chip are only now being developed. The electronics for conversion of the signals from the array of sensor elements into digital data, and the subsequent digital data processing are typically remote from the sensor element array; they are not integrated on the same chip.
Current fully digital systems provide greatly improved quality; however, the required beamforming and processing hardware is extensive, expensive, and consumes significant power. The computation necessary for beamforming is typically done by specialized high-speed digital signal processing (DSP) hardware due to the large number of arithmetic operations involved. The number of operations increases as the number of sensor elements increase.
It is desirable therefore to simplify the front end of the DAS so as to allow it to be made entirely as integrated circuitry, to reduce the number of components and the cost, to reduce the number of numeric computations required for beamforming, and to improve the beamformer time delay resolutionxe2x80x94all regardless of the number of sensor elements used.
An aggregate beamformer for use in a directional receiving array such as an array of microphones is disclosed. The aggregate beamformer selects the numerous analog signal components received from an array of input elements in a random sequence and combines them into a single sequence of oversampled signal components (aggregated) prior to providing a time alignment between the signal components according to the desired beam direction.
According to one aspect, the invention provides a beamformer for creating a virtual beam, in a desired beam direction, from an array of input signal components (input channels) obtained from an array of input elements, each input element generating an analog signal component. The beamformer comprises a sampling unit for sequentially selecting individual input analog signal components of the array in a random sequence at an oversampling rate, and outputting an aggregated digital signal comprising a single sequence of sampled digital components. An alignment unit provides a time alignment between the digital signal components, the time alignment providing coherent reinforcement of the analog signal components arriving from the desired beam direction. A sequencing unit provides the random sequence for selecting input analog signal components and the time delays for said alignment unit. A down-filter filters the time aligned signal components.
In one aspect, the down-filter comprises a digital to analog converter (DAC) for converting the digital time aligned digital signal components prior to filtering.
In another aspect, the down-filter comprises a decimator for decimating the filtered signal.
In one aspect, the sampling unit comprises a channel selector for sequentially selecting individual input analog signal components of the array in a random sequence at an oversampling rate, and an analog to digital converter (ADC) for digitizing the oversampled analog signal components to generate an aggregate digital signal comprising digital signal components.
In another aspect, the sampling unit comprises analog to digital converters (ADCs) for digitizing the individual input analog signal components of said array, and a digital channel selector for sequentially selecting in a random sequence at an oversampling rate the digital signal components to generate an aggregate digital signal comprising digital signal components.
The sequencing unit comprises a random number generator, a parameter processing unit, and a collision management unit. The parameter processing unit determines a random sequence in which the input channels are to be selected and the associated delay between successive analog signal components for a desired beam direction. The collision management unit modifies, or causes the parameter processing unit to modify, the random sequence and associated delays according to whether a collision would occur during time alignment. A collision is deemed to occur when the sequence of digital signal components already contains a data value at the position in the sequence into which the data from the selected channel would be placed with the associated time delay. A position in said sequence that does not contain a data value is called a void.
The alignment unit may be a sequencing buffer for sequencing the digital signal components in a sequenced array based on the delay between successive analog signal components as determined by the sequencing unit.
There are many advantages in using an aggregate beamformer. The beamformer is implemented with fewer components than the conventional beamformer. This is in part because, due to the high sampling rate of the random sampling process, the need for anti-alias filters is eliminated. Where the sensor bandwidth is within the oversampling rate so that the anti-alias filters can be omitted, the entire beamformer can be integrated into an IC, which may additionally include integrated sensors.
The numeric computations are restricted to the (digital) filter and are fewer than conventional beamforming when the number of elements is large. The delay resolution is greatly improved by the oversampling factor. The circuit and computational complexity do not increase significantly with the number of sensors because components such as anti-alias filters, multiple ADCs, tapped delay lines, and summers have been eliminated. The response to signal within the beam is identical to that of conventional beamformers.
The unwanted components originating elsewhere than where the beam is focused are captured as broadband noise, which is then substantially removed by the down-filter and any residual noise will not be coherent with the desired signal.
The costs for conventional beamforming scale with the number of input elements whereas they increase only marginally for the aggregate beamformer. For example, an implementation for 500 input elements would look identical to one for 8 input elements except that the multiplexer would have more inputs.
Furthermore, for a large number of input channels the digital signal processing necessary for the aggregate beamformer requires less computation than conventional beamforming; the only computations performed in the beamformer of the present invention are the filtering done prior to decimation, the random number generation (where a look-up table is not used for this purpose), and the addition of steering delays to the sequencing address, which occur at a fixed rate independent of the number of input elements.
Embodiments of the invention simplify beamforming techniques in directional array systems and help bring this technology within range of consumer product price ranges. Embodiments of the invention may be used in systems wherein a virtual beam is used for directional pickup of sound or vibration using an array of acoustic, vibration or seismic sensors. The virtual beam may be used for the construction of imagery for medical, material diagnostic, or machine intelligence purposes using an array of acoustic, electromagnetic, or optical sensors.
The aggregate beamformer can be applied to antenna arrays for digital receiving stations such as cellular telephone base stations. Since the ratio of the output (audio) bandwidth to the signal sampling rate is very high in these applications the residual noise of the aggregate beamformer will be small.
Other aspects and advantages of embodiments of the invention will be readily apparent to those ordinarily skilled in the art upon a review of the following description.